Reinforcement Learning‐Based Optimal Prescribed‐Time Tracking Control for Strict‐Feedback Systems With Unknown Affine Terms
A novel prescribed‐time optimal (PTO) tracking control scheme for nonlinear strict‐feedback systems with unknown affine terms based on radial basis function (RBF) neural networks is proposed and it is demonstrated for the first time that the critic‐actor weights can converge exponentially to the same values.